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morphology to directly link gene-regulatory cell states to functional neuronal phenotypes. This ambitious project integrates wet-lab experimentation with advanced computational analysis, and is ideal for a
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for the benefit of society through scientific excellence, innovation, and collaboration. VIB’s Data Core provides state-of-the-art data and IT services that empower life sciences research across the institute
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for the benefit of society through scientific excellence, innovation, and collaboration. VIB’s Data Core provides state-of-the-art data and IT services that empower life sciences research across the institute
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to the lack of proper techniques to study them, yet has strong translational potential. With new technologies, and the data that you will analyze, we finally have the opportunity to unlock their true potential
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discovery and innovation in biotechnology, genomics, and computational biology. At the VIB Data Core, we empower scientists by delivering advanced infrastructure and services that tackle complex challenges in
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discovery and innovation in biotechnology, genomics, and computational biology. At the VIB Data Core, we empower scientists by delivering advanced infrastructure and services that tackle complex challenges in
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works in close partnership with the Flemish universities – Ghent University, KU Leuven, University of Antwerp and Vrije Universiteit Brussel. The link between basic research and valorisation has made VIB
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. Your Role You perform quality control on sequencing data generated in-house across a variety of sequencing platforms. When suboptimal data quality or output is detected, you troubleshoot the issue and
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works in close partnership with the Flemish universities – Ghent University, KU Leuven, University of Antwerp and Vrije Universiteit Brussel. The link between basic research and valorisation has made VIB
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at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will